Image Classification
Transformers
TensorBoard
Safetensors
PyTorch
vit
huggingpics
Eval Results (legacy)
Instructions to use metadome/face_shape_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use metadome/face_shape_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="metadome/face_shape_classification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("metadome/face_shape_classification") model = AutoModelForImageClassification.from_pretrained("metadome/face_shape_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 2ff61d880ddcd1c2247b0b1a68816c07b1dbf3ce1470a966fd53aba8c9faa2e1
- Size of remote file:
- 227 kB
- SHA256:
- a89b154ef7a99b4b117ee5dfc12b5d9c797411fe3d6d9c780a3fa95aad220762
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